Office of Research and Development National Exposure Research Laboratory, Atmospheric Modeling and Analysis Division October 21, 2009 Evaluation of CMAQ.

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Office of Research and Development National Exposure Research Laboratory, Atmospheric Modeling and Analysis Division October 21, 2009 Evaluation of CMAQ v4.7 Sulfate Predictions for 2002 – 2006 K. Wyat Appel and Shawn J. Roselle 8 th Annual CMAS Conference, Chapel Hill, NC October 21, 2009

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Acknowledgements EPA (CDC PHASE Project) –Alice Gilliland –Fred Dimmick –Eric Hall –Tom Pierce –Norm Possiel –Tyler Fox EPA AMAD –Rohit Mathur –Prakash Bhave Computer Sciences Corporation –Lucille Bender –Nancy Hwang –Lara Reynolds

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory CMAQ Simulations Consistent annual simulations from km CONUS and 12-km Eastern U.S. annual simulations MM5 Meteorology with 34 vertical layers GEOS-CHEM boundary conditions –Based on 2002 GEOS-CHEM simulation –Vary monthly/spatially, but same set of monthly values used for each year Emissions based on 2002 National Emissions Inventory –Year-specific updates to fires, mobile and EGU point (CEMS data) emissions CMAQ v4.7 –24 vertical layers –CB05 Chemical Mechanism –Base model only (i.e. criteria pollutants only)

Incremental Test Periods for CMAQ v4.7 January 2006 NMdnB = -14.0% August 2006 NMB = -13.0% At the CASTNET sites, Sulfate is underpredicted in the summer of all years, with the largest overpredictions in 2002 and CASTNET SO 4 2- – 2002 through 2006

At the rural IMPROVE sites, Sulfate is underpredicted in the summer, with the largest overpredictions in 2002 and IMPROVE SO 4 2- – 2002 through

At the urban CSN sites, Sulfate is underpredicted in the summers of 2002 and 2005, but nearly unbiased in the summers of 2003, 2004 and 2006 CSN SO 4 2- – 2002 through

Since SO 4 2- is most important during the summer months, our focus has been on the summertime underprediction of SO SO 4 2- Monthly Average Normalized Mean Bias Of 180 month/network observations, only 34 show a positive bias; Of those 34, 26 occur between September and December.

NADP SO 4 2- Wet Deposition – 2002 through SO 4 2- wet deposition is only slightly overpredicted in the summer, particularly in July of 2002, 2004 and 2005.

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory NADP Precipitation – 2002 through 2006 Large positive biases in precipitation correlate to the large positive biases in SO 4 2- wet deposition in July of 2002, 2004 and However, biases in SO 4 2- wet deposition do not account for all the underprediction in ambient SO 4 2- during the summers of 2002 through 2006.

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Current/Future Work To Address Sulfate Underprediction Gas-phase sulfate production –Issues with cloud predictions –Clear-sky photolysis sensitivity

CMAQ Sulfate Predictions with Clear Sky Photolysis July 2005 Absolute DifferenceRatio Average increase at observation sites of ~ %.

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Current/Future Work To Address Sulfate Underprediction Gas-phase sulfate production –Issues with cloud predictions –Clear-sky sensitivity –Results indicate that too little gas-phase SO 4 2- production not the culprit Sulfate particle size distribution –Comparisons to MOUDI data from 2003 and 2004

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory MOUDI CMAQ See poster by Bhave et al. for more details regarding comparisons of CMAQ with MOUDI data. Sulfate particle size distribution too broad and shifted toward larger particle sizes.

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Current/Future Work To Address Sulfate Underprediction Gas-phase sulfate production –Issues with cloud predictions –Clear-sky sensitivity –Results indicate that too little gas-phase SO 4 2- production not the culprit Sulfate particle size distribution –Comparisons to MOUDI data from 2003 and 2004 –Results show particle size distribution too large and broad in some regions Sensitivity to vertical structure

Ratio of 34 layer / 14 layer CMAQ predicted sulfate SO 4 2- concentrations higher with more vertical layers. Average increase in SO 4 2- at observation sites is ~5-6%.

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Current/Future Work To Address Sulfate Underprediction Gas-phase sulfate production –Issues with cloud predictions –Clear-sky sensitivity –Results indicate that too little gas-phase SO 4 2- production not the culprit Sulfate particle size distribution –Comparisons to MOUDI data from 2003 and 2004 –Results show particle size distribution too large and broad in some regions Sensitivity to vertical structure –More vertical layers results in slightly higher SO 4 2- concentrations Vertical distribution of SO 4 2-

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Regionally-Averaged Vertical Profiles ICART Time Period (Summer 2004) Eta-CMAQ (~v4.5) 1 CMAQv4.7 SO 4 2- (ug/m 3 ) SO 2 / Total S SO 4 2- (ug/m 3 ) SO 2 / Total S Overprediction in SO 4 2- is lower with CMAQv4.7, but still largely overpredicted aloft. from Mathur et al., 2008from CDC PHASE simulations

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Current/Future Work To Address Sulfate Underprediction Gas-phase sulfate production –Issues with cloud predictions –Clear-sky sensitivity –Results indicate that too little gas-phase SO 4 2- production not the culprit Sulfate particle size distribution –Comparisons to MOUDI data from 2003 and 2004 –Results show particle size distribution too large and broad in some regions Sensitivity to vertical structure –More vertical layers results in slightly higher SO 4 2- concentrations Vertical distribution of SO 4 2- –Analyses show too much SO 4 2- aloft New cloud scheme based on Grell cloud model –Still in development

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Summary Ambient SO 4 2- underpredicted during the summer, particularly in the summers of 2002 and 2005 –Underprediction appears to be at least in part related to dry/hot summers –Summer/Fall of 2005 was an active tropical year, which may have contributed as well Ambient SO 4 2- overpredicted in the fall of 2003, 2004 and 2006 –This issue remains to be investigated, but is a lower priority than summer underprediction SO 4 2- wet deposition fairly well predicted in the summer –Some overpredictions could contribute to underpredictions in ambient SO 4 2- –However, errors in wet deposition are not the main factor contributing to underprediction in ambient SO 4 2- Near-term investigations into summertime SO 4 2- underprediction –Clear-sky photolysis sensitivity resulted in small increase in SO 4 2- –Errors in SO 4 2- particle size distribution are still being investigated –Vertical resolution plays a small role, with more vertical layers resulting in more SO 4 2- –Limited analysis showed too much SO 4 2- aloft; however, aloft prediction is improved from previous version of CMAQ. Future Work –Additional sensitivities and analysis related to meteorological predictions –Implementing a new cloud scheme (Grell) in CMAQ will force additional analysis into this issue.

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Questions? “I was gratified to be able to answer promptly. I said I don't know.” - Mark Twain

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory Supplementary Slides

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory IMPROVECSN

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory

Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory